U.S. patent number 5,513,273 [Application Number 08/219,431] was granted by the patent office on 1996-04-30 for method for obtaining information about interstitial patterns of the lungs.
This patent grant is currently assigned to Fuji Photo Film Co., Ltd.. Invention is credited to Wataru Ito.
United States Patent |
5,513,273 |
Ito |
April 30, 1996 |
Method for obtaining information about interstitial patterns of the
lungs
Abstract
For each picture element in a radiation image of the lungs, a
basic Wavelet function is rotated on the radiation image, a degree
of contraction of the basic Wavelet function is changed within a
predetermined range, and Wavelet transformation is thereby carried
out on the image signal, values of a Wavelet transformation factor
being thereby calculated. For each value of the degree of
contraction, a calculation is made to find a temporary
representative value of the values of the Wavelet transformation
factor, which have been obtained for each picture element when the
degree of contraction was fixed at a predetermined value and the
basic Wavelet function was thereby rotated on the radiation image.
For each picture element, a representative value is determined from
the temporary representative values, which have been calculated for
the values of the degree of contraction. Interstitial patterns of
the lungs are then rated in accordance with the representative
value and the value of the degree of contraction, which was
employed in the Wavelet transformation when the representative
value was determined.
Inventors: |
Ito; Wataru (Kanagawa,
JP) |
Assignee: |
Fuji Photo Film Co., Ltd.
(Kanagawa, JP)
|
Family
ID: |
26398660 |
Appl.
No.: |
08/219,431 |
Filed: |
March 17, 1994 |
Foreign Application Priority Data
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|
|
|
|
Mar 18, 1993 [JP] |
|
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5-057592 |
Mar 18, 1993 [JP] |
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5-057593 |
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Current U.S.
Class: |
382/132;
382/248 |
Current CPC
Class: |
G06T
7/42 (20170101); G06T 2207/10116 (20130101); G06T
2207/20064 (20130101); G06T 2207/30061 (20130101) |
Current International
Class: |
G06T
7/40 (20060101); G06T 007/00 () |
Field of
Search: |
;382/6,56,131,132,248
;364/413.13,413.22,413.19 ;348/77,398 ;358/426 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
Other References
Laine et al. "Wavelet Processing Techniques for Digital
Mammography," Proc. SPIE vol. 1808, Visualization in Biomedical
Computing 1992, Oct. 1992, pp. 610-624. .
Braniuk et al. "New Dimensions in Wavelet Analysis" ICASSP-92 vol.
5, Mar. 1992, pp. 137-140. .
Simoncelli et al. "Shiftable Multiscale Transforms" IEEE Trans.
Info. Theory vol. 38, No. 2, pt 2, Mar. 1992, pp. 587-607. .
Manjunath, "Gaber Wavelet Transform and Application to Problems in
Early Vision" 26th Asilomer Conf. on Sig. Sys. Comp., vol. 2, Oct.
1992, pp. 796-800. .
Peyrin et al. "Multiscale Reconstruction of Tomographic Images"
Proc. IEEE-SP Inf. Symp Time-Freq and Time-Scale Analysis, Oct.
1992, pp. 219-222. .
J. Jogoe & K. Paton, "Reading chest radiographs for
pneumoconiosis by computer," 1975, 32, pp. 267-272. .
R. Tully et al., "Towards Computer Analysis of Pulmonary
Infiltration," Jul.-Aug., 1978, vol. 13, pp. 298-305. .
R. Sutton & E. Hall, "Texture Measures for Automatic
Classification of Pulmonary Disease," IEEE Transactions on
Computers, vol. C-21, No. 7, Jul. 1972. .
T. Ishida et al., "Spectrum Analysis of Trabecular Pattern,"
Magazine of the Japan Society of Medical Imaging and Information
Sciences, vol. 9, No. 1 (1992), pp. 32-40. .
"Wavelets and Signal Processing", (Olivier Rioul and Martin
Vetterli, IEEE SP Magazine, pp. 14-38, Oct. 1991). .
"Zero-Crossings of Wavelet Transform" (Stephane Mallat, IEEE
Transactions on Information Theory vol. 37, No. 4, pp. 1019-1033,
Jul. 1991). .
"Spectral Analysis of Bone Trabecular Image--Fundamental
Experiments and Simulation" (Takigawa, et al., the Magazine of the
Japanese Society of Radialogical Technology, 1990, 9.10, pp.
1659-1669)..
|
Primary Examiner: Mancuso; Joseph
Assistant Examiner: Chang; Jon
Attorney, Agent or Firm: Sughrue, Mion, Zinn, Macpeak &
Seas
Claims
What is claimed is:
1. A method for obtaining information about interstitial patterns
of lungs from an image signal comprising picture elements and
representing a radiation image of the lungs, said method comprising
the steps of:
i) rotating, by a predetermined degree interval, a predetermined
basic Wavelet function corresponding to each of said picture
elements, and changing a degree of contraction of said basic
Wavelet function within a predetermined range to obtain a group of
values of a Wavelet transformation factor for each of said picture
elements,
ii) calculating a temporary representative value of said group of
values of said Wavelet transformation factor obtained for each of
said picture elements for a particular degree of contraction of
said basic Wavelet function within said predetermined range, said
temporary representative value being calculated for each degree of
contraction within said predetermined range of said basic Wavelet
function,
iii) selecting, for each of said picture elements, a representative
value from a plurality of temporary representative values which
have been respectively calculated for each degree of contraction of
said basic Wavelet function in step ii),
iv) determining, for each of said picture elements, interstitial
patterns of the lungs, as normal or abnormal, based upon said
representative value and a value of said degree of contraction of
said basic Wavelet function employed in the Wavelet transformation
when said representative value was determined, and
outputting results of said determining step respectively
corresponding to each of said picture elements.
2. A method as defined in claim 1, further comprising the step of
displaying an output representing said results as a lung
interstitial pattern image with one of gray level values and
colors.
3. A method as defined in claim 2, further comprising the steps
of:
setting a region having a predetermined boundary at a desired
portion on said lung interstitial pattern image,
calculating a representative value of outputs representing results
of said determining step obtained for said picture elements located
in said region, and
outputting said representative value.
4. (Amended) A method as defined in claim 1, wherein said
calculating step comprises the step of determining the mean value
of said group of values of said Wavelet transformation factor for
each of said picture elements for said particular degree of
contraction of said basic Wavelet function.
5. A method as defined in claim 4, wherein said determining step
comprises the step of determining a maximum value of a plurality of
mean values, which have been calculated for respective values,
within said predetermined range, of said degree of contraction of
said basic Wavelet function.
6. A method as defined in claim 1, further comprising the step of
storing said radiation image on a stimulable phosphor sheet prior
to said rotating step.
7. A method as defined in claim 6, further comprising the steps of
exposing said stimulable phosphor sheet storing said radiation
image to stimulating rays, which cause said stimulable phosphor
sheet to emit light in proportion to an amount of energy stored
thereon, and
photoelectrically detecting said emitted light.
8. A method as defined in claim 7, wherein said exposing step
includes the step of emitting a laser beam from a laser source.
9. A method as defined in claim 1, further comprising the step of
recording said radiation image on photographic film prior to said
rotating step.
10. A method for obtaining information about density of trabeculae
of a bone from an image signal comprising picture elements and
representing a radiation image of an object containing the bone,
said method comprising the steps of:
i) rotating by a predetermined degree interval, a predetermined
basic Wavelet function corresponding to each of said picture
elements, and changing a degree of contraction of said basic
Wavelet function within a predetermined range to obtain a group of
values of a Wavelet transformation factor for each of said picture
elements,
ii) calculating a representative value from said group of values of
said Wavelet transformation factor obtained for each of said
picture elements; and
iii) obtaining said information about said density of the
trabeculae of the bone in accordance with a value of said degree of
contraction of said basic Wavelet function employed in said Wavelet
transformation when said representative value was calculated.
11. A method as defined in claim 10, further comprising the step of
displaying said information about said density of the trabeculae of
the bone as a bone trabecula density image with one of gray level
values and colors.
12. A method as defined in claim 11, further comprising the steps
of:
setting a region having a predetermined boundary at a desired
portion on said bone trabecula density image,
calculating a representative value of values of said degree of
contraction of said basic Wavelet function employed in said Wavelet
transformation when respective representative values of said groups
of values of said Wavelet transformation factor were obtained in
step i) for said picture elements located in said region, and
outputting said representative value.
13. A method as defined in claim 10, wherein said calculating step
comprises the step of determining a maximum value of said group of
said values of said Wavelet transformation factor for each of said
picture elements.
14. A method as defined in claim 10, further comprising the step of
storing said radiation image on a stimulable phosphor sheet prior
to said rotating step.
15. A method as defined in claim 14, further comprising the steps
of exposing said stimulable phosphor sheet storing said radiation
image to stimulating rays, which cause said stimulable phosphor
sheet to emit light in proportion to an amount of energy stored
thereon, and
photoelectrically detecting said emitted light.
16. A method as defined in claim 15, wherein said exposing step
includes the step of emitting a laser beam from a laser source.
17. A method as defined in claim 10, further comprising the step of
recording said radiation image on photographic film prior to said
rotating step.
Description
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to a method for obtaining information about
interstitial patterns of the lungs, which information is to be
utilized in making a diagnosis of the lung tissues. This invention
also relates to a method for obtaining information about density of
trabeculae of a bone of a human body, or the like, which
information is to be utilized in making a diagnosis of an
osteoporosis.
2. Description of the Prior Art
Techniques for reading out a recorded radiation image in order to
obtain an image signal, carrying out appropriate image processing
on the image signal, and then reproducing a visible image by use of
the processed image signal have heretofore been known in various
fields. For example, an X-ray image is recorded on an X-ray film
having a small gamma value chosen according to the type of image
processing to be carried out, the X-ray image is read out from the
X-ray film and converted into an electric signal (i.e., an image
signal), and the image signal is processed and then used for
reproducing the X-ray image as a visible image on a photocopy, or
the like. In this manner, a visible image having good image quality
with high contrast, high sharpness, high graininess, or the like,
can be reproduced.
Also, it has been proposed to use stimulable phosphors in radiation
image recording and reproducing systems. Specifically, a radiation
image of an object, such as a human body, is recorded on a sheet
provided with a layer of the stimulable phosphor (hereinafter
referred to as a stimulable phosphor sheet). The stimulable
phosphor sheet, on which the radiation image has been stored, is
then scanned with stimulating rays, such as a laser beam, which
cause it to emit light in proportion to the amount of energy stored
thereon during its exposure to the radiation. The light emitted by
the stimulable phosphor sheet, upon stimulation thereof, is
photoelectrically detected and converted into an electric image
signal. The image signal is then processed and used for the
reproduction of the radiation image of the object as a visible
image on a recording material.
In the radiation image recording and reproducing systems wherein
recording media, such as X-ray film or stimulable phosphor sheets,
are used, various kinds of image processings are ordinarily carried
out on the detected image signal such that a visible image may be
reproduced which has good image quality and can serve as an
effective tool in, particularly, the efficient and accurate
diagnosis of an illness.
Also, with the radiation image recording and reproducing systems
wherein recording media, such as X-ray film or stimulable phosphor
sheets, are used, a radiation image of the chest of a human body is
obtained and utilized in making a diagnosis of a disease of the
lungs of the human body. Specifically, image signal components
representing the image patterns of the lungs are sampled from the
image signal representing the chest image. Also, the position of a
region of interest is determined, and the state of a disease of the
lungs in the region of interest is investigated.
Of the diseases of the lungs of human bodies, which diseases are
thus found, interstitial diseases, i.e. interstitial abnormal
states in the ventricles of the lungs due to accumulation of
liquids or protein substances, occur most frequently. Examinations
of the interstitial diseases of the lungs reach 40% of the X-ray
examinations carried out in hospitals in the United States of
America. For example, it has been reported that 22% of the abnormal
states of the lungs found with the recording of X-ray images of the
chests in the Medical Center of Chicago University are due to
interstitial abnormal states.
The rating of interstitial diseases utilizing the X-ray photographs
of the chests is the most difficult technique in the
radiotherapeutics. This is because various patterns and complicated
displacements are encountered in the interstitial diseases, because
the relationship between radiological findings and pathological
findings has not yet been established, and because the terms used
in order to express X-ray image patterns have not yet been defined
clearly and vary for different experts in the radiology. Therefore,
the manner, in which interstitial patterns of the lungs are rated,
vary for different persons, organizations, and the like. Also, even
if the interstitial patterns of the lungs are rated by a single
person, the results of the rating will vary for different time and
circumstances. Accordingly, accurate diagnoses of interstitial
diseases of the lungs could not be made in the past.
In view of the above circumstances, various methods have been
proposed wherein interstitial patterns of the lungs are
quantitatively determined such that the interstitial patterns can
be rated objectively. For example, a method for rating the
interstitial patterns of the lungs in accordance with statistical
properties of a density distribution in an X-ray image has been
proposed by Sutton in "IEEE Transactions on Computers," Vol. C-21,
No. 7, July 1972. Also, a method for obtaining power spectra of the
lung tissues by use of engineering Fourier transformation and
discriminating between the normal lungs and the lungs affected by
interstitial diseases has been proposed by Tully, et al. in
"Investigative Radiology," July-August, 1978, Vol. 13, pp. 298-305.
Further, a method, wherein tissue patterns are encoded in
accordance with the directions of gray level gradient vectors,
which are determined by carrying out a sampling operation on an
X-ray photograph of the chest at 1.2 mm sampling intervals, such
that the severity of a pneumoconiosis may be investigated, has been
proposed by Jagoe, et al in "British Journal of Industrial
Medicine," 1975, 32, pp. 267-272.
However, the proposed methods have the problems in that, in cases
where the contrast of the patterns due to an interstitial disease
is low, a small change in density on the X-ray photograph is lost,
and therefore an accurate diagnosis of the interstitial disease of
the lungs cannot be made. Such that these problems may be
eliminated, a novel method has been proposed in Japanese Unexamined
Patent Publication No. 1(1989)-125675. The proposed method
comprises the steps of setting a region of interest on a chest
image, removing image signal components, which represent the
background information, from the image signal components
corresponding to the region of interest, processing the image
signal components, which are now free of the background
information, with a spectral analysis, and thereby automatically
detecting and assaying the interstitial patterns. With the proposed
method, the coarseness or fineness of a texture can be expressed by
the level and the root-mean-square value (rms value) of the
first-order moment of a power spectrum obtained from the spectral
analysis. Therefore, the state of an interstitial disease of the
lungs can be expressed quantitatively.
However, with the method proposed in Japanese Unexamined Patent
Publication No. 1(1989)-125675, the region having a predetermined
range is set on a radiation image, and the mean-level spectrum in
the predetermined range is obtained. Therefore, of the information
representing the radiation image, only the information
corresponding to the predetermined range can be obtained.
Accordingly, with the proposed method, local spectral analyses of
interstitial patterns of the lungs cannot be carried out. Also,
with the proposed method wherein the spectral analysis is carried
out, the region is set manually. Therefore, the problems often
occur in that the region is set at an incorrect location. In such
cases, accurate information about the interstitial patterns of the
lungs cannot be obtained, and the severity of a disease of the lung
fields cannot be found accurately. Further, with the proposed
method wherein the background information must be removed from the
image signal, the calculation time cannot be kept short.
Recently, with the rapid increase in the number of aged persons,
osteoporosis has become a medical and social important problem. It
has been indicated that the early detection and early diagnosis are
of great importance in osteoporosis as in various other diseases.
In order for the osteoporosis to be detected early, it is necessary
to make a system, with which examinations of a large number of
persons can be carried out easily and accurately such that the
bodily and economical burdens to the persons may be kept as light
as possible.
A conventional method for making a diagnosis of the osteoporosis
will be described hereinbelow. The conventional method is referred
to as the Jidai's classification method. With the conventional
method, the severity of the osteoporosis is classified as shown in
FIGS. 10A, 10B, 10C, 10D, and 10E in accordance with the
impressions which a physician received during observation of,
primarily, the trabeculae of a vertebral bone or the density of the
image pattern of the vertebral bone. Specifically, FIG. 10A shows
an X-ray image of a normal vertebral body, which has dense
longitudinal and transverse bone trabecula patterns. FIG. 10B shows
an X-ray image of the vertebral body having osteoporosis in its
initial stage, in which the image density of the bone is lower as a
whole than the image density of the X-ray image shown in FIG. 10A,
and in which the patterns of the trabeculae of the bone are thinner
and smaller than those shown in FIG. 10A. FIGS. 10C, 10D, and 10E
respectively show X-ray images of the vertebral bodies having the
osteoporosis in its stages of degree I, degree II, and degree III.
As the degree of the osteoporosis becomes higher, the densities of
the bone trabeculae in the longitudinal and transverse directions
become lower. In this manner, the abnormal states in the images of
the trabeculae of the bones are rated with four ranks, i.e. the
initial stage, degree I, degree II, and degree III. However, with
this method for making a diagnosis of osteoporosis, which relies
upon the physician's subjective point of view, the state of the
trabeculae of the bone cannot be ascertained quantitatively.
In view of the above circumstances, a method has been proposed,
wherein an image signal representing a radiation image of a bone is
subjected to spectral analysis utilizing the fast Fourier transform
(FFT) and the maximum entropy method (MEM), and the patterns of
trabeculae of the bone are numerically expressed with a peak
spatial frequency and a power spectrum value. Such a method is
described in, for example, "Spectral Analysis of Bone Trabecula
Image--Fundamental Experiments and Simulation," by Takigawa, et al
, the Magazine of the Japanese Society of Radiological Technology,
1990, 9.10, pp. 1659-1669. Also, a method has been proposed,
wherein a power spectrum of a bone image is obtained, and
information about the density of trabeculae of the bone is analyzed
in accordance with the RMS value (the amount of fluctuation in
image density) and the first-order moment (the coarseness and
fineness of the image), which are obtained from the power spectrum.
Such a method is described in, for example, "Spectral Analysis of
Trabecular Pattern," the Magazine Vol. 9, No. 1 (1992), pp.
32-40.
With the aforesaid methods utilizing the spectral analyses, errors
in making diagnoses of the osteoporosis can be prevented from
occurring due to dependence upon the physician's subjective point
of view, and the information about the density of a bone,
particularly the bone trabeculae, can be obtained
quantitatively.
However, with the aforesaid methods utilizing the spectral
analyses, a region of a predetermined range is set on the radiation
image, and the mean-level spectrum in the predetermined range is
obtained. Therefore, of the information representing the radiation
image, only the information corresponding to the predetermined
range can be obtained. Accordingly, with the aforesaid methods
utilizing the spectral analyses, local spectral analyses of bone
images cannot be carried out. Also, with the aforesaid methods
utilizing the spectral analyses, wherein the spectral analyses are
carried out, the region is set manually. Therefore, the problems
often occur in that the region is set at an incorrect location. In
such cases, accurate information about the density of the
trabeculae of the bone cannot be obtained.
SUMMARY OF THE INVENTION
The primary object of the present invention is to provide a method
for obtaining information about interstitial patterns of the lungs,
wherein a predetermined region need not be set in a lung image, and
local information about the interstitial patterns of the lungs can
be obtained quickly and accurately from the lung image.
Another object of the present invention is to provide a method for
obtaining information about density of trabeculae of a bone,
wherein a predetermined region need not be set in a bone image, and
local information about the density of the trabeculae of the bone
can be obtained accurately from the bone image.
The present invention provides a first method for obtaining
information about interstitial patterns of the lungs from an image
signal representing a radiation image of the lungs as an object,
comprising the steps of:
i) for each of picture elements in the radiation image, rotating a
predetermined basic Wavelet function on the radiation image and
changing a degree of contraction of the basic Wavelet function
within a predetermined range of the degree of contraction, whereby
Wavelet transformation is carried out on the image signal, a group
of values of a Wavelet transformation factor being thereby
calculated for each of the picture elements in the radiation
image,
ii) calculating a temporary representative value of the group of
the values of the Wavelet transformation factor, which have been
obtained for each of the picture elements in the radiation image
when the degree of contraction of the basic Wavelet function was
fixed at a predetermined value and the basic Wavelet function was
thereby rotated on the radiation image, the calculation of the
temporary representative value being made for each of the values of
the degree of contraction of the basic Wavelet function,
iii) for each of the picture elements in the radiation image,
determining a representative value from a plurality of the
temporary representative values, which have been calculated for the
values of the degree of contraction of the basic Wavelet function,
and
iv) for each of the picture elements in the radiation image, rating
the interstitial patterns of the lungs in accordance with the
determined representative value and the value of the degree of
contraction of the basic Wavelet function, which contraction degree
value was employed in the Wavelet transformation when the
representative value was determined, the results of the rating
being thereafter fed out as an output.
The present invention also provides a second method for obtaining
information about interstitial patterns of the lungs, wherein the
first method for obtaining information about interstitial patterns
of the lungs in accordance with the present invention is modified
such that the outputs representing the results of the ratings of
the interstitial patterns of the lungs, which outputs have been
obtained for the picture elements in the radiation image, are
displayed as a lung interstitial pattern image with gray level
values or colors.
The present invention further provides a third method for obtaining
information about interstitial patterns of the lungs, wherein the
second method for obtaining information about interstitial patterns
of the lungs in accordance with the present invention is modified
such that a region having a predetermined range is set at a desired
portion on the lung interstitial pattern image, which is displayed
by the second method for obtaining information about interstitial
patterns of the lungs in accordance with the present invention,
a calculation is made to find a representative value of the outputs
representing the results of the ratings, which outputs have been
obtained for the picture elements located in the region, and
the representative value of the outputs is fed out as the
information about the interstitial patterns of the lungs.
The present invention still further provides a first method for
obtaining information about density of trabeculae of a bone from an
image signal representing a radiation image of an object containing
the bone, comprising the steps of:
i) for each of picture elements in the radiation image, rotating a
predetermined basic Wavelet function on the radiation image and
changing a degree of contraction of the basic Wavelet function
within a predetermined range of the degree of contraction, whereby
Wavelet transformation is carried out on the image signal, a group
of values of a Wavelet transformation factor being thereby
calculated for each of the picture elements in the radiation
image,
ii) calculating a representative value from the group of the values
of the Wavelet transformation factor, which have been obtained for
each of the picture elements in the radiation image, and
iii) obtaining the information about the density of the trabeculae
of the bone in accordance with the value of the degree of
contraction of the basic Wavelet function, which contraction degree
value was employed in the Wavelet transformation when the
representative value was calculated.
The present invention also provides a second method for obtaining
information about density of trabeculae of a bone, wherein the
first method for obtaining information about density of trabeculae
of a bone in accordance with the present invention is modified such
that the information about the density of the trabeculae of the
bone, which information has been obtained for the picture elements
in the radiation image, is displayed as a bone trabecula density
image with gray level values or colors.
The present invention further provides a third method for obtaining
information about density of trabeculae of a bone, wherein the
second method for obtaining information about density of trabeculae
of a bone in accordance with the present invention is modified such
that a region having a predetermined range is set at a desired
portion on the bone trabecula density image, which is displayed by
the second method for obtaining information about density of
trabeculae of a bone in accordance with the present invention,
a calculation is made to find a representative value of the values
of the degree of contraction of the basic Wavelet function, which
contraction degree values were employed in the Wavelet
transformation when the representative values of the groups of the
values of the Wavelet transformation factor were obtained for the
picture elements located in the region, and
the representative value of the values of the degree of contraction
of the basic Wavelet function is fed out as the information about
the density of the trabeculae of the bone.
How the Wavelet transformation is carried out will be described
hereinbelow.
The Wavelet transformation has recently been developed as a
frequency analysis method and has heretofore been applied to stereo
pattern matching, signal compression, and the like. The Wavelet
transformation is described in, for example, "Wavelets and Signal
Processing," by Olivier Rioul and Martin Vetterli, IEEE SP
Magazine, pp. 14-38, October 1991; and "Zero-Crossings of a Wavelet
Transform," by Stephane Mallat, IEEE Transactions on Information
Theory, Vol. 37, No. 4, pp. 1019-1033, July 1991.
With the Wavelet transformation, a signal is transformed into
frequency signals, each being of one of a plurality of different
frequency bands, by utilizing a function h, which is shown in FIG.
6, as a basic function and in accordance with the formula ##EQU1##
wherein f(t): the signal having an arbitrary wave form, W(a,b): the
Wavelet transformation of f(t), ##EQU2## a: the degree of
contraction of the function, b: the amount of movement in the
horizontal axis direction.
Therefore, the problems with regard to a false oscillation, which
occurs with Fourier transformation, do not occur. Specifically,
when filtering processing is carried out by changing the period and
the degree of contraction of the function h and moving the function
h on an original signal, frequency signals, each of which is
adapted to one of desired frequencies ranging from a fine frequency
to a coarse frequency. By way of example, FIG. 7 shows signals,
which are obtained by carrying out the Wavelet transformation on an
original signal Sorg and then carrying out inverse Wavelet
transformation for each of frequency bands. FIG. 8 shows signals,
which are obtained by carrying out Fourier transformation on the
original signal Sorg and then carrying out inverse Fourier
transformation for each of the frequency bands. As will be
understood from FIGS. 7 and 8, the Wavelet transformation has the
advantage over the Fourier transformation in that a frequency
signal of a frequency band corresponding to the oscillation of the
original signal Sorg can be obtained. Specifically, with the
Fourier transformation, an oscillation occurs in a part A' of a
frequency band 7, which corresponds to a part A of the original
signal Sorg. However, with the Wavelet transformation, as in the
original signal Sorg, no oscillation occurs in a part B' of a
frequency band W7, which corresponds to a part B of the original
signal Sorg.
With the method for obtaining information about interstitial
patterns of the lungs in accordance with the present invention, for
each of the picture elements in the radiation image of the lung
tissues as an object, the predetermined basic Wavelet function is
rotated on the radiation image, the degree of contraction of the
basic Wavelet function is changed within a predetermined range, and
the Wavelet transformation is thereby carried out on the image
signal representing the radiation image. In this manner, a group of
values of the Wavelet transformation factor are calculated for each
of the picture elements in the radiation image. Specifically, the
degrees of coincidence between portions of the radiation image
around each of the picture elements and the basic Wavelet function
are obtained as the group of the values of the Wavelet
transformation factor by rotating the basic Wavelet function and
changing the degree of contraction of the basic Wavelet function.
In this manner, the values of the Wavelet transformation factor
adapted to the directions, in which the densities of the object
image portions around each of the picture elements vary, and the
values of the densities can be obtained by rotating the basic
Wavelet function with respect to each of the picture elements and
changing the degree of contraction of the basic Wavelet function
within a predetermined range. Also, the values of the Wavelet
transformation factor of the radiation image, which is free of
noise, i.e. the high frequency components in the radiation image,
and the information representing the background, i.e. the low
frequency components in the radiation image, can be obtained by
limiting the change in the degree of contraction of the basic
Wavelet function to the predetermined range.
With the method for obtaining information about interstitial
patterns of the lungs in accordance with the present invention,
thereafter, a calculation is made to find the temporary
representative value of the group of the values of the Wavelet
transformation factor, which have been obtained for each of the
picture elements in the radiation image when the degree of
contraction of the basic Wavelet function was fixed at a
predetermined value and the basic Wavelet function was thereby
rotated on the radiation image. The calculation of the temporary
representative value is made for each of the values of the degree
of contraction of the basic Wavelet function. Specifically, the
degree of contraction of the basic Wavelet function is fixed with
respect to each of the picture elements, and the basic Wavelet
function is thereby rotated such that the values of the Wavelet
transformation factor with respect to respective directions at the
fixed degree of contraction of the basic Wavelet function may be
obtained. Thereafter, the temporary representative value, which is
representative of the values of the Wavelet transformation factor
with respect to respective directions, is calculated. In this
manner, adverse effects of the directions of the densities of
linear object image portions around each of the picture elements
can be eliminated, and the information about the values of the
densities around each of the picture elements can be obtained as
the temporary representative value regardless of the difference in
the value of the Wavelet transformation factor due to the
difference in the direction of the density of the linear object
image portion. In the manner described above, for each of the
picture elements in the radiation image, a plurality of the
temporary representative values are obtained for the values of the
degree of contraction of the basic Wavelet function.
Thereafter, with the method for obtaining information about
interstitial patterns of the lungs in accordance with the present
invention, for each of the picture elements in the radiation image,
the representative value is determined from the plurality of the
temporary representative values, which have been calculated for the
values of the degree of contraction of the basic Wavelet function.
Specifically, with respect to each of the picture elements in the
radiation image, the value of the Wavelet transformation factor
corresponding to the value of the degree of contraction, at which
the degree of coincidence between the object image portions around
each of the picture elements and the basic Wavelet function was
highest, is thereby determined for each of the picture elements in
the radiation image. Thereafter, for each of the picture elements
in the radiation image, the interstitial patterns of the lungs in
the radiation image are rated in accordance with the determined
representative value and the value of the degree of contraction of
the basic Wavelet function, which contraction degree value was
employed in the Wavelet transformation when the representative
value was determined. Also, the results of the rating is fed out as
an output.
In cases where the value of the degree of contraction of the basic
Wavelet function, which contraction degree value was employed in
the Wavelet transformation when the representative value was
determined, is small, it may be judged that the density of the lung
interstitial patterns located at the image portions around the
corresponding picture element is high. Also, in cases where the
value of the degree of contraction of the basic Wavelet function,
which contraction degree value was employed in the Wavelet
transformation when the representative value was determined, is
large, it may be judged that the density of the lung interstitial
patterns located at the image portions around the corresponding
picture element is low. In this manner, the information about the
interstitial patterns of the lungs can be obtained.
Also, with the method for obtaining information about interstitial
patterns of the lungs in accordance with the present invention, the
information about the interstitial patterns of the lungs may be
displayed as a lung interstitial pattern image with gray level
values or colors in accordance with the determined representative
value and the value of the degree of contraction of the basic
Wavelet function, which contraction degree value was employed in
the Wavelet transformation when the representative value was
determined. In this manner, the interstitial patterns of the lungs
can be seen as a visible image.
As described above, with the method for obtaining information about
interstitial patterns of the lungs in accordance with the present
invention, when the information about the interstitial patterns of
the lungs is to be obtained, no region need be set in the radiation
image. Therefore, a manual operation for setting a region in the
radiation image need not be carried out, and the accuracy, with
which the information about the interstitial patterns of the lungs
is obtained, can be prevented from becoming low due to a mistake
made in the setting of such a region. Also, with the method for
obtaining information about interstitial patterns of the lungs in
accordance with the present invention, the information about the
interstitial patterns of the lungs can be obtained with respect to
the entire area of the lung image. Therefore, local analyses of the
interstitial patterns of the lungs can be carried out. Further, a
particular operation for eliminating the information representing
the background in the radiation image need not be carried out, and
therefore the time required to carry out the operations can be kept
short.
Furthermore, with the method for obtaining information about
interstitial patterns of the lungs in accordance with the present
invention, the interstitial patterns of the lungs can be displayed
as a lung interstitial pattern image with gray level values or
colors in accordance with the differences in the values of the
degree of contraction of the basic Wavelet function. Therefore, the
severity of a disease in the lung fields can be investigated
easily.
With the method for obtaining information about density of
trabeculae of a bone in accordance with the present invention, for
each of the picture elements in the radiation image of an object
containing the bone, the predetermined basic Wavelet function is
rotated on the radiation image, the degree of contraction of the
basic Wavelet function is changed within a predetermined range, and
the Wavelet transformation is thereby carried out on the image
signal representing the radiation image. In this manner, a group of
values of the Wavelet transformation factor are calculated for each
of the picture elements in the radiation image. Specifically, the
degrees of coincidence between portions of the radiation image
around each of the picture elements and the basic Wavelet function
are obtained as the group of the values of the Wavelet
transformation factor by rotating the basic Wavelet function and
changing the degree of contraction of the basic Wavelet function.
In this manner, the values of the Wavelet transformation factor
adapted to the directions, in which the densities of the object
image portions around each of the picture elements vary, and the
values of the densities can be obtained by rotating the basic
Wavelet function with respect to each of the picture elements and
changing the degree of contraction of the basic Wavelet function
within a predetermined range. Also, with the method for obtaining
information about density of trabeculae of a bone in accordance
with the present invention, wherein the change in the degree of
contraction of the basic Wavelet function is limited to the
predetermined range, the Wavelet transformation is not carried out
with respect to noise, i.e. the high frequency components, in the
radiation image, and the information representing the background,
i.e. the low frequency components, in the radiation image.
Therefore, the values of the Wavelet transformation factor of the
radiation image, which is free of noise and the information
representing the background, can be obtained.
With the method for obtaining information about density of
trabeculae of a bone in accordance with the present invention,
thereafter, the representative value is calculated from the group
of the values of the Wavelet transformation factor, which have been
obtained for each of the picture elements in the radiation image.
Specifically, with respect to each of the picture elements in the
radiation image, the value of the Wavelet transformation factor
corresponding to the value of the degree of contraction, at which
the degree of coincidence between the object image portions around
each of the picture elements and the basic Wavelet function was
highest, is thereby determined for each of the picture elements in
the radiation image. Thereafter, the information about the density
of the trabeculae of the bone is obtained in accordance with the
value of the degree of contraction of the basic Wavelet function,
which contraction degree value was employed in the Wavelet
transformation when the representative value was calculated.
In cases where the value of the degree of contraction of the basic
Wavelet function, which contraction degree value was employed in
the Wavelet transformation when the representative value was
determined, is small, it may be judged that the density of the
trabeculae of the bone located at the image portions around the
corresponding picture element is high. Also, in cases where the
value of the degree of contraction of the basic Wavelet function,
which contraction degree value was employed in the Wavelet
transformation when the representative value was determined, is
large, it may be judged that the density of the trabeculae of the
bone located at the image portions around the corresponding picture
element is low. In this manner, the information about the density
of the trabeculae of the bone can be obtained.
Also, with the method for obtaining information about density of
trabeculae of a bone in accordance with the present invention, the
information representing the density of the trabeculae of the bone,
which information has been obtained for the picture elements in the
radiation image, may be displayed as a bone trabecula density image
with gray level values or colors in accordance with the value of
the degree of contraction of the basic Wavelet function, which
contraction degree value was employed in the Wavelet transformation
when the representative value was calculated for each of the
picture elements in the radiation image. In this manner, the
density of the trabeculae of the bone can be viewed as a visible
image.
As described above, with the method for obtaining information about
density of trabeculae of a bone in accordance with the present
invention, when the information about the density of the trabeculae
of the bone is to be obtained, no region need be set in the
radiation image. Therefore, a manual operation for setting a region
in the radiation image need not be carried out, and the accuracy,
with which the information about the density of the trabeculae of
the bone is obtained, can be prevented from becoming low due to a
mistake made in the setting of such a region. Also, with the method
for obtaining information about density of trabeculae of a bone in
accordance with the present invention, the information about the
density of the trabeculae of the bone can be obtained with respect
to the entire area of the bone image. Therefore, local analyses of
the density of the trabeculae of the bone can be carried out.
Further, with the method for obtaining information about density of
trabeculae of a bone in accordance with the present invention, the
density of the trabeculae of the bone can be displayed as a bone
trabecula image with gray level values or colors in accordance with
the differences in the values of the degree of contraction of the
basic Wavelet function. Therefore, the level of the density of the
trabeculae of the bone can be investigated easily.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a block diagram showing the fundamental concept behind
the method for obtaining information about interstitial patterns of
the lungs in accordance with the present invention,
FIG. 2 is a perspective view showing an example of a radiation
image read-out apparatus,
FIG. 3 is an explanatory view showing a basic Wavelet function,
FIG. 4 is a graph showing the relationship between a degree of
contraction of the basic Wavelet function and a Wavelet
transformation factor,
FIG. 5 is a graph showing the relationship between a degree of
contraction of the basic Wavelet function and a Wavelet
transformation factor,
FIG. 6 is a graph showing the basic Wavelet function for Wavelet
transformation,
FIG. 7 is a diagram showing signals, which are obtained by carrying
out the Wavelet transformation on an original signal Sorg and then
carrying out inverse Wavelet transformation for each of frequency
bands,
FIG. 8 is a diagram showing signals, which are obtained by carrying
out Fourier transformation on the original signal Sorg and then
carrying out inverse Fourier transformation for each of the
frequency bands,
FIG. 9 is a block diagram showing the fundamental concept behind
the method for obtaining information about density of trabeculae of
a bone in accordance with the present invention,
FIG. 10A is a schematic view showing an X-ray image of a normal
vertebral body, and
FIGS. 10B, 10C, 10D, and 10E are schematic views showing X-ray
images of the vertebral bodies having the osteoporosis in its
various stages.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
The present invention will hereinbelow be described in further
detail with reference to the accompanying drawings.
First, embodiments of the method for obtaining information about
interstitial patterns of the lungs in accordance with the present
invention will be described hereinbelow.
FIG. 1 is a block diagram showing the fundamental concept behind
the method for obtaining information about interstitial patterns of
the lungs in accordance with the present invention.
As illustrated in FIG. 1, in the method for obtaining information
about interstitial patterns of the lungs in accordance with the
present invention, an image signal representing a radiation image
of the lungs as an object is obtained in a step 1. Thereafter, in a
step 2, for each of picture elements in the radiation image, a
predetermined basic Wavelet function is rotated on the radiation
image, a degree of contraction of the basic Wavelet function is
changed within a predetermined range, and Wavelet transformation is
thereby carried out on the image signal. In this manner, a group of
values of a Wavelet transformation factor are calculated for each
of the picture elements in the radiation image. In a step 3, a
calculation is made to find a temporary representative value of the
group of the values of the Wavelet transformation factor, which
have been obtained for each of the picture elements in the
radiation image when the degree of contraction of the basic Wavelet
function was fixed at a predetermined value and the basic Wavelet
function was thereby rotated on the radiation image. The
calculation of the temporary representative value is made for each
of the values of the degree of contraction of the basic Wavelet
function. Then, in a step 4, for each of the picture elements in
the radiation image, a representative value is determined from a
plurality of the temporary representative values, which have been
calculated for the values of the degree of contraction of the basic
Wavelet function. In a step 5, for each of the picture elements in
the radiation image, rating is carried out as to the determined
representative value and the value of the degree of contraction of
the basic Wavelet function, which contraction degree value was
employed in the Wavelet transformation when the representative
value was determined. In this manner, in a step 6, information
about interstitial patterns of the lungs is obtained.
An embodiment of the method for obtaining information about
interstitial patterns of the lungs in accordance with the present
invention will hereinafter be described in detail.
FIG. 2 is a perspective view showing an example of a radiation
image read-out apparatus.
In a radiation image recording apparatus (not shown), a radiation
image is stored on a stimulable phosphor sheet 14. The stimulable
phosphor sheet 14, on which the radiation image has been stored, is
then set at a predetermined position in a read-out apparatus
20.
After the stimulable phosphor sheet 14, on which the radiation
image has been stored, is set at the predetermined position in the
read-out apparatus 20, the stimulable phosphor sheet 14 is conveyed
in a sub-scanning direction indicated by the arrow Y by an endless
belt 22, which is operated by a motor 21. A laser beam 24 is
produced by a laser beam source 23 and is reflected and deflected
by a rotating polygon mirror 26, which is quickly rotated by a
motor 25 in the direction indicated by the arrow. The laser beam 24
then passes through a converging lens 27, which may be constituted
of an f.theta. lens, or the like. The direction of the optical path
of the laser beam 24 is then changed by a mirror 28, and the laser
beam 24 impinges upon the stimulable phosphor sheet 14 and scans it
in a main scanning direction indicated by the arrow X, which
direction is approximately normal to the sub-scanning direction
indicated by the arrow Y. When the stimulable phosphor sheet 14 is
exposed to the laser beam 24, the exposed portion of the stimulable
phosphor sheet 14 emits light 29 in an amount proportional to the
amount of energy stored thereon during its exposure to radiation.
The emitted light 29 is guided by a light guide member 30 and
photoelectrically detected by a photomultiplier 31. The light guide
member 30 is made from a light guiding material, such as an acrylic
plate, and has a linear light input face 30a, positioned so that it
extends along the main scanning line on the stimulable phosphor
sheet 14, and a ring-shaped light output face 30b, positioned so
that it is in close contact with a light receiving face of the
photomultiplier 31. The emitted light 29, which has entered the
light guide member 30 at its light input face 30a, is guided
through repeated total reflection inside of the light guide member
30, emanates from the light output face 30b, and is received by the
photomultiplier 31. In this manner, the amount of the emitted light
29, which amount represents the radiation image, is converted into
an electric signal by the photomultiplier 31.
An analog output signal SO generated by the photomultiplier 31 is
logarithmically amplified by a logarithmic amplifier 32 and
digitized by an A/D converter 33 into an image signal Sorg. The
image signal Sorg is then fed into an image processing unit 40. The
image processing unit 40 comprises a CRT display device 41 which
reproduces and displays a visible image, a main body 42 in which a
CPU, an internal memory, interfaces, and the like, are
incorporated, a floppy disk drive unit 43 which operates a floppy
disk, and a keyboard 44 from which necessary instructions, or the
like, are fed into the image processing unit 40.
In the image processing unit 40, the information about the
interstitial patterns of the lungs is obtained in the manner
described below.
First, the Wavelet transformation is carried out on the image
signal Sorg by using a predetermined basic Wavelet function.
Specifically, an x axis is set along the main scanning direction on
the radiation image. Also, a y axis is set along the sub-scanning
direction on the radiation image. The coordinates of each of
picture elements in the radiation image are represented by (x,y),
and the value of the image signal component representing each of
the picture elements is represented by S(x,y). In such cases, the
Wavelet transformation is carried out with Formula (2) ##EQU3##
wherein ##EQU4## Vb represents the vector b, which represents the
amount of movement on the x-y plane, a represents the degree of
contraction of the function h(x,y), and T(a,r,Vb) represents the
Wavelet transformation factor.
The function h(x,y) is expressed by level lines as shown in FIG. 3.
With respect to each of the picture elements in the radiation
image, the function h(x,y) is rotated with the parameter r around a
point P, the value of the degree of contraction a of the function
h(x,y) is changed, and the Wavelet transformation is thereby
carried out. From the Wavelet transformation, the degrees of
coincidence between the function h(x,y) and the image portions
around each picture element having the coordinates (x,y) are
obtained as the values of the Wavelet transformation factor
T(a,r,Vb), wherein Vb represents the vector b.
First, the value of the degree of contraction a of the function
h(x,y) is fixed at a predetermined value, and the function h(x,y)
is rotated a total angle of 360 degrees at intervals of, for
example, 10 degrees around the point P. Each time the function
h(x,y) is rotated an angle of 10 degrees, the Wavelet
transformation is carried out with Formula (2). After the function
h(x,y) has been rotated one turn, the value of the degree of
contraction a of the function h(x,y) is changed to values at
predetermined intervals of 2.sup.N times the previous value. For
each value of the degree of contraction a, the function h(x,y) is
rotated, and the Wavelet transformation is carried out with Formula
(2). If the value of the degree of contraction a is very small, the
values of the Wavelet transformation factor of the radiation image
containing noise, i.e. the high frequency components of the
radiation image, will be obtained. If the value of the degree of
contraction a is very large, the values of the Wavelet
transformation factor of the radiation image containing the
information representing the background, i.e. the low frequency
components of the radiation image, will be obtained. In order for
these problems to be eliminated, the value of the degree of
contraction a is changed in a range such that it may not coincide
with the frequencies of noise and the information representing the
background.
In the manner described above, the function h(x,y) is rotated, the
value of the degree of contraction a of the function h(x,y) is
changed, and the Wavelet transformation is thereby carried out.
From the Wavelet transformation, the value of the Wavelet
transformation factor T(a,r,Vb) is obtained for each rotation angle
and for each value of the degree of contraction a.
Thereafter, a calculation is made to find the mean value of the
group of the values of the Wavelet transformation factor, which
have been obtained for each of the picture elements in the
radiation image when the degree of contraction a of the function
h(x,y) was fixed at a predetermined value and the function h(x,y)
was thereby rotated various angles on the radiation image. The mean
value is represented by ##EQU5##
The mean value is calculated for each of the values of the degree
of contraction a of the function h(x,y), which are employed for
each of the picture elements in the radiation image. In this
manner, a plurality of the mean values of the groups of the values
of the Wavelet transformation factor, which groups have been
obtained for the respective values of the degree of contraction a
employed for each of the picture elements in the radiation image,
are calculated. Therefore, even if linear image portions are
embedded in the radiation image, adverse effects of the directions
of the linear image portions can be eliminated, and the information
about the values of the densities around each of the picture
elements can be obtained as the mean value regardless of the
difference in the value of the Wavelet transformation factor due to
the difference in the direction of the density of the linear image
portion.
Thereafter, for each picture element having the coordinates (x,y),
the maximum value of the mean values, which have been calculated
for the values of the degree of contraction a, is calculated. The
maximum value is expressed as ##EQU6##
Each of the mean values is the mean value of the group of the
values of the Wavelet transformation factor for each of the values
of the degree of contraction a of the basic Wavelet function, which
contraction degree values are employed for each of the picture
elements in the radiation image. Therefore, the maximum value of
the mean values of the groups of the values of the Wavelet
transformation factor, which groups have been calculated for
different values of the degree of contraction a, is calculated with
respect to each of the picture elements in the radiation image in
accordance with the level of the density of the interstitial
patterns of the lungs. Specifically, as for an image portion at
which the interstitial patterns of the lungs are present densely,
the mean value of the group of the values of the Wavelet
transformation factor obtained with a small value of the degree of
contraction a is calculated as the maximum value. Also, as for an
image portion at which the interstitial patterns of the lungs are
present sparsely, the mean value of the group of the values of the
Wavelet transformation factor obtained with a large value of the
degree of contraction a is calculated as the maximum value.
As described above, the Wavelet transformation is carried out by
rotating the function h(x,y) with the parameter r. Therefore, even
if the interstitial patterns of the lungs in the lung image are not
parallel to the x axis or the y axis on the radiation image and are
inclined with respect to the x axis or the y axis, the function
h(x,y) can follow the inclination of the interstitial patterns of
the lungs. Accordingly, the maximum value of the mean values of the
groups of the values of the Wavelet transformation factor can be
calculated in accordance with the level of the density of the
interstitial patterns of the lungs and regardless of the
inclination of the interstitial patterns of the lungs.
Therefore, the relationship between the maximum value, which has
been calculated in the manner described above, and the value of the
degree of contraction a of the function h(x,y), which contraction
degree value was employed in the Wavelet transformation when the
maximum value was calculated, is investigated. FIG. 4 is a graph
showing the relationship between the value of the degree of
contraction a and the maximum value. In the graph of FIG. 4 showing
the relationship between the value of the degree of contraction a
and the maximum value, the region indicated by the white circles
indicates an abnormal state, and the region indicated by the black
dots indicates the normal state. Specifically, in cases where the
value of the degree of contraction a is large and the maximum value
is comparatively large, the interstitial patterns of the lungs are
in an abnormal state. In cases where the value of the degree of
contraction a is small and the maximum value is comparatively
small, the interstitial patterns of the lungs are in the normal
state. Therefore, for every picture element in the radiation image,
the relationship between the value of the degree of contraction a
and the maximum value is plotted on the graph shown in FIG. 4. If
the plotted point is located in the region indicated by the white
circles, it may be judged that the portion corresponding to the
plotted point is in an abnormal state. If the plotted point is
located in the region indicated by the black dots, it may be judged
that the portion corresponding to the plotted point is in the
normal state.
Rating of the interstitial patterns of the lungs is carried out in
the manner described above. Therefore, a predetermined region need
not be set in the radiation image. Accordingly, the accuracy, with
which the information about the interstitial patterns of the lungs
is obtained, can be prevented from becoming low due to a mistake
made in the setting of such a region. Also, the information about
the interstitial patterns of the lungs can be viewed easily, and
the severity of a disease in the lung fields can be investigated
easily.
Also, the interstitial patterns of the lungs can be expressed as
levels of image density in accordance with the results of the
plotting on the graph. Specifically, as illustrated in FIG. 5, a
plurality of regions A, B, C, D, E, and F are set on the graph
showing the relationship between the value of the degree of
contraction a and the maximum value. Thereafter, the relationship
between the calculated maximum value and the corresponding value of
the degree of contraction a is plotted on the graph. Rating is then
made as to whether the plotted point falls within the region A, B,
C, D, E, or F. The lowest image density is assigned to the region
A, the highest image density is assigned to the region F, and
intermediate levels of image density are assigned to the regions B,
D, E, and E. In this manner, for each picture element having the
coordinates (x,y), the level of the image density corresponding to
the region, in which the corresponding relationship between the
value of the degree of contraction a and the maximum value was
plotted, is set. The levels of the image density, which have thus
been set for the picture elements in the radiation image, are
displayed as a lung interstitial pattern image. In the lung
interstitial pattern image, a portion in which the interstitial
patterns of the lungs are in an abnormal state is indicated by a
high level of image density, and a portion in which the
interstitial patterns of the lungs are in the normal state is
indicated by a low level of image density. Therefore, the normal
state and the abnormal state of the interstitial patterns of the
lungs can be displayed as the levels of image density.
As described above, the state of the interstitial patterns of the
lungs can be displayed with image density values on a visible
image, and the interstitial patterns of the lungs in the entire
area of the radiation image can be viewed. Therefore, local
interstitial patterns of the lungs can be investigated from the
information representing the entire area of the radiation
image.
In the embodiment described above, the information about the
interstitial patterns of the lungs is displayed as a gray level
image in accordance with the relationship between the maximum
value, which has been calculated for each of the picture elements
in the radiation image, and the value of the degree of contraction
of the basic Wavelet function, which contraction degree value was
employed in the Wavelet transformation when the maximum value was
calculated. Alternatively, the interstitial patterns of the lungs
may be displayed with colors in accordance with the differences in
the values of the degree of contraction of the basic Wavelet
function.
Specifically, in the graph shown in FIG. 5, blue, green, red,
yellow, and so on, may be set in accordance with the distance from
the origin, i.e. from the region A towards the region F. The
information about the interstitial patterns of the lungs may then
be displayed as a lung interstitial pattern image with colors
according to the region, in which the relationship between the
value of the degree of contraction a and the maximum value was
plotted for each picture element having the coordinates (x,y). In
this manner, the state of the interstitial patterns of the lungs
can be displayed by colors.
After the information about the interstitial patterns of the lungs
has been displayed as the lung interstitial pattern image with the
gray level values or colors, a region having a predetermined range
may be set at a desired portion on the lung interstitial pattern
image. A calculation may then be made to find the mean value of the
values of the degree of contraction a, which are represented by the
levels of image density or the colors in the set region. The mean
value thus calculated may then be fed out as a value representing
the information about the interstitial patterns of the lungs. In
such cases, the interstitial patterns of the lungs are displayed
with the gray level values or colors on the lung interstitial
pattern image and can be easily ascertained on the lung
interstitial pattern image. Therefore, the setting of the region
can be carried out accurately.
Also, in the embodiment described above, the Wavelet transformation
is carried out by changing the value of the degree of contraction a
to values at predetermined intervals. Alternatively, the Wavelet
transformation may be carried out by changing the value of the
degree of contraction a to continuously varying values.
Further, in the embodiment described above, the mean value of the
group of the values of the Wavelet transformation factor is
employed as the temporary representative value for each value of
the degree of contraction a. Alternatively, the n'th order moment
with respect to the rotation parameter may be employed as the
temporary representative value.
Furthermore, in the embodiment described above, the maximum value
of the mean values of the groups of the values of the Wavelet
transformation factor is employed as the representative value,
which is representative of the groups of the values of the Wavelet
transformation factor for each of the picture elements in the
radiation image. Alternatively, the n'th order moment with respect
to the degree of contraction a may be employed as the
representative value.
Moreover, in the embodiment described above, the mean value of the
values of the degree of contraction a, which are represented by the
levels of image density or the colors in the region having the
predetermined range on the lung interstitial pattern image, is
employed as the representative value, which is representative of
the levels of image density or the colors in the region.
Alternatively, the n'th order moment with respect to the degree of
contraction a may be employed as the representative value, which is
representative of the levels of image density or the colors in the
region.
Embodiments of the method for obtaining information about density
of trabeculae of a bone in accordance with the present invention
will be described hereinbelow.
FIG. 9 is a block diagram showing the fundamental concept behind
the method for obtaining information about density of trabeculae of
a bone in accordance with the present invention.
As illustrated in FIG. 9, in the method for obtaining information
about density of trabeculae of a bone in accordance with the
present invention, an image signal representing a radiation image
of an object containing a bone is obtained in a step 101.
Thereafter, in a step 102, for each of picture elements in the
radiation image, a predetermined basic Wavelet function is rotated
on the radiation image, a degree of contraction of the basic
Wavelet function is changed within a predetermined range, and
Wavelet transformation is thereby carried out on the image signal.
In this manner, a group of values of a Wavelet transformation
factor are calculated for each of the picture elements in the
radiation image. In a step 103, for each of the picture elements in
the radiation image, a representative value is calculated from the
group of the values of the Wavelet transformation factor. In a step
104, the value of the degree of contraction of the basic Wavelet
function, which contraction degree value was employed in the
Wavelet transformation when the representative value was
calculated, is found. Thereafter, in a step 105, the information
about the density of the trabeculae of the bone is obtained in
accordance with the value of the degree of contraction, which has
been found in the step 104.
An embodiment of the method for obtaining information about density
of trabeculae of a bone in accordance with the present invention
will hereinafter be described in detail.
In a radiation image recording apparatus (not shown), a radiation
image is stored on a stimulable phosphor sheet 14. The stimulable
phosphor sheet 14, on which the radiation image has been stored, is
fed into the radiation image read-out apparatus shown in FIG. 2.
The stimulable phosphor sheet 14 is set at a predetermined position
in the read-out apparatus 20, and the radiation image is read out
from the stimulable phosphor sheet 14 in the same manner as that
described above.
An analog output signal SO generated by the photomultiplier 31 is
logarithmically amplified by the logarithmic amplifier 32 and
digitized by the A/D converter 33 into an image signal Sorg. The
image signal Sorg is then fed into the image processing unit
40.
In the image processing unit 40, the information about the density
of the trabeculae of the bone is obtained in the manner described
below.
First, the Wavelet transformation is carried out on the image
signal Sorg by using a predetermined basic Wavelet function.
Specifically, an x axis is set along the main scanning direction on
the radiation image. Also, a y axis is set along the sub-scanning
direction on the radiation image. The coordinates of each of
picture elements in the radiation image are represented by (x,y),
and the value of the image signal component representing each of
the picture elements is represented by S(x,y). In such cases, the
Wavelet transformation is carried out with Formula (2) ##EQU7##
wherein ##EQU8## Vb represents the vector b, which represents the
amount of movement on the x-y plane, a represents the degree of
contraction of the function h(x,y), and T(a,r,Vb) represents the
Wavelet transformation factor.
The function h(x,y) is expressed by level lines as shown in FIG. 3.
With respect to each of the picture elements in the radiation
image, the function h(x,y) is rotated with the parameter r around a
point P, the value of the degree of contraction a of the function
h(x,y) is changed, and the Wavelet transformation is thereby
carried out. From the Wavelet transformation, the degrees of
coincidence between the function h(x,y) and the image portions
around each picture element having the coordinates (x,y) are
obtained as the values of the Wavelet transformation factor
T(a,r,Vb), wherein Vb represents the vector b.
First, the function h(x,y) is rotated a total angle of 360 degrees
at intervals of, for example, 10 degrees around the point P. Each
time the function h(x,y) is rotated an angle of 10 degrees, the
Wavelet transformation is carried out with Formula (2) by changing
the value of the degree of contraction a of the function h(x,y) to
values at predetermined intervals of 2.sup.N times the previous
value. If the value of the degree of contraction a is very small,
the values of the Wavelet transformation factor of the radiation
image containing noise, i.e. the high frequency components of the
radiation image, will be obtained. If the value of the degree of
contraction a is very large, the values of the Wavelet
transformation factor of the radiation image containing the
information representing the background, i.e. the low frequency
components of the radiation image, will be obtained. In order for
these problems to be eliminated, the value of the degree of
contraction a is changed in a range such that it may not coincide
with the frequencies of noise and the information representing the
background.
In the manner described above, the function h(x,y) is rotated, the
value of the degree of contraction a of the function h(x,y) is
changed, and the Wavelet transformation is thereby carried out.
From the Wavelet transformation, the value of the Wavelet
transformation factor T(a,r,Vb) is obtained for each rotation angle
and for each value of the degree of contraction a.
Thereafter, for each picture element having the coordinates (x,y),
the maximum value of the values of the Wavelet transformation
factor T(a,r,Vb), which have been obtained for the respective
rotation angles and for the values of the degree of contraction a,
is calculated. The maximum value is expressed as ##EQU9##
As described above, the function h(x,y) is rotated around the point
P, and the value of the degree of contraction a is changed.
Therefore, the maximum value of the values of the Wavelet
transformation factor, which have been calculated for different
values of the degree of contraction a, is calculated with respect
to each of the picture elements in the radiation image in
accordance with the level of the density of the patterns of the
trabeculae of the bone shown in FIGS. 10A, 10B, 10C, 10D, and 10E.
Specifically, as for an image portion at which the trabeculae of
the bone are present densely, the value of the Wavelet
transformation factor obtained with a small value of the degree of
contraction a is calculated as the maximum value. Also, as for an
image portion at which the trabeculae of the bone are present
sparsely, the value of the Wavelet transformation factor obtained
with a large value of the degree of contraction a is calculated as
the maximum value.
As described above, the Wavelet transformation is carried out by
rotating the function h(x,y) with the parameter r. Therefore, even
if the longitudinal and transverse patterns of the trabeculae of
the bone in the bone image are not parallel to the x axis or the y
axis on the radiation image and are inclined with respect to the x
axis or the y axis, the function h(x,y) can follow the inclination
of the patterns of the trabeculae of the bone. Accordingly, the
maximum value of the values of the Wavelet transformation factor
can be calculated in accordance with the level of the density of
the trabeculae of the bone and regardless of the inclination of the
patterns of the trabeculae of the bone.
As described above, the value of the degree of contraction a of the
function h(x,y), which contraction degree value was employed in the
Wavelet transformation when the maximum value of the values of the
Wavelet transformation factor was calculated, is small for an image
portion, at which the patterns of the trabeculae of the bone are
present densely, and is large for an image portion, at which the
patterns of the trabeculae of the bone are present sparsely.
Therefore, the value of the image density at each picture element
having the coordinates (x,y) may be displayed as a bone trabecula
density image in accordance with the value of the degree of
contraction a of the function h(x,y), which contraction degree
value was employed in the Wavelet transformation when the maximum
value of the values of the Wavelet transformation factor was
calculated. For example, in cases where the value of the degree of
contraction a is small, a large image density value may be
employed. In cases where the value of the degree of contraction a
is large, a small image density value may be employed. In this
manner, a portion at which the trabeculae of the bone are present
densely is displayed with a large image density value, and a
portion at which the trabeculae of the bone are present sparsely is
displayed with a small image density value. Therefore, the level of
the density, at which the trabeculae of the bone are present, can
be expressed with the level of the image density.
As described above, the levels of the density, at which the
trabeculae of the bone are present, can be displayed with image
density values on a visible image, and the sparseness and denseness
of the patterns of the trabeculae of the bone can be viewed
easily.
Also, the levels of the density of the trabeculae of the bone in
the entire area of the radiation image can be viewed. Therefore,
the level of local density of the trabeculae of the bone can be
investigated from the information representing the entire area of
the radiation image.
Further, a predetermined region need not be set in the radiation
image. Therefore, the accuracy, with which the information about
the density of the trabeculae of the bone is obtained, can be
prevented from becoming low due to a mistake made in the setting of
such a region.
In the aforesaid embodiment of the method for obtaining information
about density of trabeculae of a bone in accordance with the
present invention, the information about the density of the
trabeculae of the bone is displayed as a gray level image in
accordance with the value of the degree of contraction of the basic
Wavelet function, which contraction degree value was employed in
the Wavelet transformation when the representative value for each
of the picture elements in the radiation image was calculated.
Alternatively, the information about the density of the trabeculae
of the bone may be displayed with colors in accordance with the
differences in the values of the degree of contraction of the basic
Wavelet function.
After the information about the density of the trabeculae of the
bone has been displayed as the bone trabecula density image with
the gray level values or colors, a region having a predetermined
range may be set at a desired portion on the bone trabecula density
image. A calculation may then be made to find the mean value of the
values of the degree of contraction a, which are represented by the
levels of image density or the colors in the set region. The mean
value thus calculated may then be fed out as a value representing
the information about the density of the trabeculae of the bone. In
such cases, the information about the density of the trabeculae of
the bone is displayed with the gray level values or colors on the
bone trabecula density image, and the level of the density of the
trabeculae of the bone can be easily ascertained on the bone
trabecula density image. Therefore, the setting of the region can
be carried out accurately.
Also, in the aforesaid embodiment of the method for obtaining
information about density of trabeculae of a bone in accordance
with the present invention, the Wavelet transformation is carried
out by changing the value of the degree of contraction a to values
at predetermined intervals. Alternatively, the Wavelet
transformation may be carried out by changing the value of the
degree of contraction a to continuously varying values.
Further, in the aforesaid embodiment of the method for obtaining
information about density of trabeculae of a bone in accordance
with the present invention, the maximum value of the values of the
Wavelet transformation factor is employed as the representative
value, which is representative of the values of the Wavelet
transformation factor for each of the picture elements in the
radiation image. Alternatively, the n'th order moment with respect
to the degree of contraction a may be employed as the
representative value.
Moreover, in the aforesaid embodiment of the method for obtaining
information about density of trabeculae of a bone in accordance
with the present invention, the mean value of the values of the
degree of contraction a, which are represented by the levels of
image density or the colors in the region having the predetermined
range on the bone trabecula density image, is employed as the
representative value, which is representative of the levels of
image density or the colors in the region. Alternatively, the n'th
order moment with respect to the degree of contraction a may be
employed as the representative value, which is representative of
the levels of image density or the colors in the region.
* * * * *